Welcome to the InfoSci Platform
Object Detection Methods for Improving Smart City Safety

Object Detection Methods for Improving Smart City Safety

Kavita Srivastava
Copyright: © 2022 |Pages: 20
ISBN13: 9781799897101|ISBN10: 1799897109|ISBN13 Softcover: 9781799897118|EISBN13: 9781799897125
DOI: 10.4018/978-1-7998-9710-1.ch011
Cite Chapter Cite Chapter

MLA

Srivastava, Kavita. "Object Detection Methods for Improving Smart City Safety." Advances in Deep Learning Applications for Smart Cities, edited by Rajeev Kumar and Rakesh Kumar Dwivedi, IGI Global, 2022, pp. 228-247. https://doi.org/10.4018/978-1-7998-9710-1.ch011

APA

Srivastava, K. (2022). Object Detection Methods for Improving Smart City Safety. In R. Kumar & R. Dwivedi (Eds.), Advances in Deep Learning Applications for Smart Cities (pp. 228-247). IGI Global. https://doi.org/10.4018/978-1-7998-9710-1.ch011

Chicago

Srivastava, Kavita. "Object Detection Methods for Improving Smart City Safety." In Advances in Deep Learning Applications for Smart Cities, edited by Rajeev Kumar and Rakesh Kumar Dwivedi, 228-247. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-9710-1.ch011

Export Reference

Mendeley
Favorite

Abstract

The safety measures in a city are of major concern to its people. A smart surveillance system is necessary to make the safety measures robust and reliable. Currently, there are many object detection methods available for image analysis. Image analysis is only possible when we can detect the number of objects in the image, type of objects, as well as their location. Image analysis methods include Fast RCNN, YOLO, region-based convolution neural network (RCNN), and so on. These object detection methods are based on deep learning (DL) techniques. Video analysis requires the detection of moving objects. These methods involve background subtraction and extracting the foreground objects for motion analysis. There are several deep learning (DL)-based methods for video analysis such as the YOLO algorithm for detecting objects in a video frame and identifying their location. This chapter describes significant object detection methods in images and video that can be used in surveillance systems to improve the safety measures in a city.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.